Bangqian Chen

Mapping forests in monsoon Asia with ALOS PALSAR 50-m mosaic images and MODIS imagery in 2010.

Extensive forest changes have occurred in monsoon Asia, substantially affecting climate, carbon cycle and biodiversity. Accurate forest cover maps at fine spatial resolutions are required to qualify and quantify these effects. In this study, an algorithm was developed to map forests in 2010, with the use of structure and biomass information from the Advanced Land Observation System (ALOS) Phased Array L-band Synthetic Aperture Radar (PALSAR) mosaic dataset and the phenological information from MODerate Resolution Imaging Spectroradiometer (MOD13Q1 and MOD09A1) products. Our forest map (PALSARMOD50 m F/NF) was assessed through randomly selected ground truth samples from high spatial resolution images and had an overall accuracy of 95%. Total area of forests in monsoon Asia in 2010 was estimated to be ~6.3 × 106 km2. The distribution of evergreen and deciduous forests agreed reasonably well with the median Normalized Difference Vegetation Index (NDVI) in winter. PALSARMOD50 m F/NF map showed good spatial and areal agreements with selected forest maps generated by the Japan Aerospace Exploration Agency (JAXA F/NF), European Space Agency (ESA F/NF), Boston University (MCD12Q1 F/NF), Food and Agricultural Organization (FAO FRA), and University of Maryland (Landsat forests), but relatively large differences and uncertainties in tropical forests and evergreen and deciduous forests.

On the ratio of intercellular to ambient CO 2 ( c i / c a ) derived from ecosystem flux

The ratio of intercellular to ambient CO2 concentrations (ci/ca) plays a key role in ecophysiology, micrometeorology, and global climatic change. However, systematic investigation on ci/ca variation and its determinants are rare. Here, the ci/ca was derived from measuring ecosystem fluxes in an even-aged monoculture of rubber trees (Hevea brasiliensis). We tested whether ci/ca is constant across environmental gradients and if not, which dominant factors control ci/ca variations. Evidence indicates that ci/ca is not a constant. The ci/ca exhibits a clear “V”-shaped diurnal pattern and varies across the environmental gradient. Water vapor pressure deficit (D) is the dominant factor controls over the ci/ca variations. ci/ca consistently decreases with increasing D. ci/ca decreases with square root of D as predicted by the optimal stomatal model. The D-driving single-variable model could simulate ci/ca as well as that of sophisticated model. Many variables function on longer timescales than a daily cycle, such as soil water content, could improve ci/ca model prediction ability. Ecosystem flux can be effectively used to calculate ci/ca and use it to better understand various natural cycles.

Components of Soil Respiration and Its Monthly Dynamics in Rubber Plantation Ecosystems

Our objective was to quantify four components and study effect factors of soil respiration in rubber plantation ecosystems. Providing the basic data support for the establishment of the trade of rubber plantation ecosystem carbon source/sink. We used Li-6400 (IRGA, Li-COR) to quantitate four components of soil respiration in rubber plantation ecosystems at different ages. Soil respiration can be separated as four components: heterotrophic respiration (Rh), respiration of roots (Rr), respiration of litter layer (Rl) and respiration of mineral soil (Rm). The soil respiration rate (Rs) showed significant seasonal variation. The maximum soil respiration rate of the whole year appeared in August, and the minimum in November or December. The components of soil respiration rate order showed as: heterotrophic respiration>respiration of roots>respiration of litter layer>respiration of mineral soil. The soil respiration rate was highly significant correlation (p<;0.01, Q10=1.13~2.37) with 0~10 cm soil temperature in dry season, and significant correlation (p<;0.05, Q10=1.10~1.77) with 0~10cm soil temperature in wet season. And soil respiration rate was not significant correlation with soil water content of 5 cm (p≥0.05). The soil respiration components of four kinds forest ages accounted for the percentage contribution to the flux of annual carbon emissions (Rs) as: Rh: 35.28~52.75%, Rr: 21.73~39.97%, Rl: 17.13~19.63%, Rm: 6.605~10.27%%, respectively. The soil respiration rate carbon flux of 5a, 10a, 19a and 33a respectively were 10.03, 10.34, 11.96 and 11.09 t·hm-2·a-1. And the annual carbon flux of soil respiration increased with stand ages increasing in rubber plantation ecosystems.

Spatial-temporal consistency between gross primary productivity and solar-induced chlorophyll fluorescence of vegetation in China during 2007–2014

Accurately estimating spatial-temporal patterns of gross primary production (GPP) is important for the global carbon cycle. Satellite-based light use efficiency (LUE) models are regarded as an efficient tool in simulating spatial-temporal dynamics of GPP. However, the accuracy assessment of GPP simulations from LUE models at both spatial and temporal scales remains a challenge. In this study, we simulated GPP of vegetation in China during 2007-2014 using a LUE model (Vegetation Photosynthesis Model, VPM) based on MODIS (moderate-resolution imaging spectroradiometer) images with 8-day temporal and 500-m spatial resolutions and NCEP (National Center for Environmental Prediction) climate data. Global Ozone Monitoring Instrument 2 (GOME-2) solar-induced chlorophyll fluorescence (SIF) data were used to compare with VPM simulated GPP (GPPVPM) temporally and spatially using linear correlation analysis. Significant positive linear correlations exist between monthly GPPVPM and SIF data over a single year (2010) and multiple years (2007-2014) in most areas of China. GPPVPM is also significantly positive correlated with GOME-2 SIF (R2 > 0.43) spatially for seasonal scales. However, poor consistency was detected between GPPVPM and SIF data at yearly scale. GPP dynamic trends have high spatial-temporal variation in China during 2007-2014. Temperature, leaf area index (LAI), and precipitation are the most important factors influence GPPVPM in the regions of East Qinghai-Tibet Plateau, Loss Plateau, and Southwestern China, respectively. The results of this study indicate that GPPVPM is temporally and spatially in line with GOME-2 SIF data, and space-borne SIF data have great potential for evaluating LUE-based GPP models.

Identifying Establishment Year and Pre-Conversion Land Cover of Rubber Plantations on Hainan Island, China Using Landsat Data during 1987–2015

Knowing the stand age of rubber tree (Hevea brasiliensis) plantations is vitally important for best management practices, estimations of rubber latex yields, and carbon cycle studies (e.g., biomass, carbon pools, and fluxes). However, the stand age (as estimated from the establishment year of rubber plantation) is not available across large regions. In this study, we analyzed Landsat time series images from 1987–2015 and developed algorithms to identify (1) the establishment year of rubber plantations; and (2) the pre-conversion land cover types, such as old rubber plantations, evergreen forests, and cropland. Exposed soil during plantation establishment and linear increases in canopy closure during non-production periods (rubber seedling to mature plantation) were used to identify the establishment year of rubber plantations. Based on the rubber plantation map for 2015 (overall accuracy = 97%), and 1981 Landsat images since 1987, we mapped the establishment year of rubber plantations on Hainan Island (R2 = 0.85/0.99, and RMSE = 2.34/0.54 years at pixel/plantation scale). The results show that: (1) significant conversion of croplands and old rubber plantations to new rubber plantations has occurred substantially in the northwest and northern regions of Hainan Island since 2000, while old rubber plantations were mainly distributed in the southeastern inland strip; (2) the pattern of rubber plantation expansion since 1987 consisted of fragmented plantations from smallholders, and there was no tendency to expand towards a higher altitude and steep slope regions; (3) the largest land source for new rubber plantations since 1988 was old rubber plantations (1.26 × 105 ha), followed by cropland (0.95 × 105 ha), and evergreen forests (0.68 × 105 ha). The resultant algorithms and maps of establishment year and pre-conversion land cover types are likely to be useful in plantation management, and ecological assessments of rubber plantation expansion in China. Remote Sens. 2018, 10, 1240; doi:10.3390/rs10081240 www.mdpi.com/journal/remotesensing Remote Sens. 2018, 10, 1240 2 of 23

Integrated Analyses of PALSAR and Landsat Imagery Reveal More Agroforests in a Typical Agricultural Production Region, North China Plain

As the largest among terrestrial ecosystems, forests are vital to maintaining ecosystem services and regulating regional climate. The area and spatial distribution of trees in densely forested areas have been focused on in the past few decades, while sparse forests in agricultural zones, so-called agroforests or trees outside forests (TOF), have usually been ignored or missed in existing forest mapping efforts, despite their important role in regulating agricultural ecosystems. We combined Landsat and PALSAR data to map forests in a typical agricultural zone in the North China Plain. The resultant map, based on PALSAR and Landsat (PL) data, was also compared with five existing medium resolution (30–100 m) forest maps from PALSAR (JAXA forest map) and Landsat: NLCD-China, GlobeLand30, ChinaCover, and FROM-GLC. The results show that the PL-based forest map has the highest accuracy (overall accuracy of 95 ± 1% with a 95% confidence interval, and Kappa coefficient of 0.86) compared to those forest maps based on single Landsat or PALSAR data in the North China Plain (overall accuracy ranging from 85 ± 2% to 92 ± 1%). All forest maps revealed higher accuracy in densely forested mountainous areas, while the PL-based and JAXA forest maps showed higher accuracy in the plain, as the higher omission errors existed in only the Landsat-based forest maps. Moreover, we found that the PL-based forest map can capture more patched forest information in low forest density areas. This means that the radar data have advantages in capturing forests in the typical agricultural zones, which tend to be missing in published Landsat-based only forest maps. Given the significance of agroforests in regulating ecosystem services of the agricultural ecosystem and improving carbon stock estimation, this study implies that the integration of PALSAR and Landsat data can provide promising agroforest estimates in future forest inventory efforts, targeting a comprehensive understanding of ecosystem services of agroforests and a more accurate carbon budget inventory.

Expansion dynamics of deciduous rubber plantations in Xishuangbanna, China during 2000–2010

Monoculture rubber plantations have been replacing tropical rain forests substantially in Southern China and Southeast Asia over the past several decades, which have affected human wellbeing and ecosystem services. However, to the best of our knowledge on the extent of rubber plantation expansion and their stand ages is limited. We tracked the spatiotemporal dynamics of deciduous rubber plantations in Xishuangbanna, the second largest natural rubber production region in China, from 2000 to 2010 using time-series data from the Phased Array type L-band Synthetic Aperture Radar (PALSAR), Landsat, and Moderate Resolution Imaging Spectroradiometer (MODIS). We found that rubber plantations have been expanding across a gradient from the low-elevation plains to the high elevation mountains. The areas of deciduous rubber plantations with stand ages ≤5, 6–10, and ≥11-year old were ~1.2 × 105 ha, ~0.8 × 105 ha, and ~2.9 × 105 ha, respectively. Older rubber plantations were mainly located in low-elevation and species-rich regions (500–900 m) and younger rubber trees were distributed in areas of relative high-elevation with fragile ecosystems. Economic and market factors have driven the expansion of rubber plantations, which is not only a threat to biodiversity and environmental sustainability, but also a trigger for climatic disasters. This study illustrates that the integration of microwave, optical, and thermal data is an effective method for mapping deciduous rubber plantations in tropical mountainous regions and determining their stand ages. Our results demonstrate the spatiotemporal pattern of rubber expansions over the first decade of this century.